Conference Paper

Efficient Data Trading and Storage in Internet of Vehicles using Consortium Blockchain

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  • Edo State University Iyamho
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... In view of the current security threats in the V2X systems, the proposed secure communication models and identification technologies include: utilizing the blockchain-based multi-factor authentication models to enhance identification mechanism [7]; using the elliptic curve encryption-based digital signature scheme to strengthen the safe interaction of V2X data information [8]; security authentication between cross-layer and cloud platforms based on cryptographic algorithm technology such as national secret algorithm [9]; utilizing various access security mutual trust authentication protocols simultaneously integrating 5G technology for secure communication of the Internet of Vehicles [10]; using third-party security modules such as cloud servers and certificate servers to authenticate users to protect the confidentiality and integrity of information [11]; etc. ...
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In recent years, Dedicated Short-Range Communication (DSRC) vehicle interconnection technology has achieved mature development and broad applications, which is the key Vehicle to Everything (V2X) technology to realize transport intelligence. However, the openness of wireless transmission and the mobility of wireless terminals cause the identification mechanism of the DSRC system to face serious security threats. A radio frequency fingerprint (RFF)-based identification method can better resist the identity attack and spoofing by extracting the hardware characteristics formed by the differences of electronic components to authenticate different devices. Therefore, in this paper a novel RFF identification mechanism is proposed for IEEE 802.11p protocol-based DSRC intelligent vehicle networking devices suitable for a high mobility environment, in which the preamble field features of physical layer frames are extracted as device fingerprints, and the random forest algorithm and sequential detection method are used to distinguish and authenticate different devices. The experiment and simulation results demonstrate that the identification accuracy rates of the eight DSRC modules in the low-speed LOS and NLOS experimental states and up to 70 km/h high-speed simulations all exceed 99%, illustrating that this method has important application value in the field of identity authentication of V2X devices in high-speed scenarios.
... Despite valuable contributions for individual subsystems of an open system for data trading, only a few studies allow for conclusions regarding the combined use of DLT and VANETs for data trading between X-Nodes (e.g., [5,84]). Existing research mainly approached the challenge of limited communication time in VANETs using simulations (e.g., [85]). ...
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Communication between vehicles and their environment (i.e., vehicle-to-everything or V2X communication) in vehicular ad hoc networks (VANETs) has become of particular importance for smart cities. However, economic challenges, such as the cost incurred by data sharing (e.g., due to power consumption), hinder the integration of data sharing in open systems into smart city applications, such as dynamic environmental zones. Moving from open data sharing to open data trading can address the economic challenges and incentivize vehicle drivers to share their data. In this context, integrating distributed ledger technology (DLT) into open systems for data trading is promising for reducing the transaction cost of payments in data trading, avoiding dependencies on third parties, and guaranteeing openness. However, because the integration of DLT conflicts with the short available communication time between fast moving objects in VANETs, it remains unclear how open data trading in VANETs using DLT should be designed to be viable. In this work, we present a system design for data trading in VANETs using DLT. We measure the required communication time for data trading between a vehicle and a roadside unit in a real scenario and estimate the associated cost. Our results show that the proposed system design is technically feasible and economically viable.
... However, due to the lack of centralized management in decentralized data market, its system design and security assurance will be more difficult than centralized data market. For example, double payment has always been the difficulty of distributed system [6,7]. ...
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With the increasing utilization of space related data, the demand for spatial big data sharing and trading is growing rapidly, which promotes the emergence of spatial data market. However, in conventional data markets, both data buyers and data sellers have to use a centralized trading platform which might be dishonest. Blockchain is a decentralized distributed data storage technology, which uses the traceability and unforgeability to confirm and record each transaction, can solve the disadvantages of the centralized data market, however, it also introduces the problems of security and privacy. To address this issue, we propose a blockchain-based spatial data trading framework with Trusted Execution Environment to provide a trusted decentralized platform, including data storage, data query, data pricing and security computing. Based on this framework, a spatial data trading demonstration system was implemented and its feasibility and security were verified.
... During the payment mechanism in P2P trading, new accounts are generated by using the account mapping technique to collect coins, which depends on a predefined criteria. Moreover, based on the previous work [16], the data storage issue is solved using InterPlanetary File system (IPFS) (briefly explained in Section II-D), and blockchain is integrated in IoEV for trading transparency. We aim to design a trustful, secure E-trading and D-trading with reliable data storage system. ...
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The drastic increase in real-time vehicle generated data of various types has imparted a great concept of data trading in vehicular networks. Whereas immense usage of Electric Vehicles (EVs) as mobile energy carriers have supported distributed energy trading due to their bidirectional charging and discharging capabilities. The trustless environment of Internet of Electric Vehicles (IoEV), including fuel vehicles and EVs, encounters trading disputes and conflicting interests among trading parties. To address these challenges, we exploit consortium blockchain to maintain transparency and trust in trading activities. Smart contracts are used to tackle trading disputes and illegal actions. Data duplication problem occurs when a dishonest user sell previously traded data multiple times for financial gain. Therefore, data duplication validation is done through previously stored hash-list at roadside units (RSUs) employed with bloom filters for efficient data lookup. Removing data duplication at an earlier stage reduces storage cost. Moreover, an elliptic curve bilinear pairing based digital signature scheme is used to ensure the reliability and integrity of traded data. To ensure persistent availability of traded data, InterPlanetary File System (IPFS) is used, which provides fault-tolerant and a reliable data storage without any single point of failure. On the other hand, the energy trading transactions among EVs face some security and privacy protection challenges. An adversary can infer the energy trading records of EVs, and launch the data linkage attacks. To address this issue, an account generation technique is used that hides the energy trading trends. The new account generation for an EV depends upon its traded volume of energy. The experimental results verify the efficiency of the proposed data and energy trading scheme in IoEV with the reliable and secure data storage.
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With the continuous growth in the amount of data generated in the edge-cloud environment, security risks in traditional centralized data management platforms have been concerned. Blockchain technology can be applied to guarantee safety and information transparency in data caching and trading processes. Therefore, a blockchain-based secure cost-aware data caching scheme is proposed to optimize the placement and prevent the tampering of cache data. In this scheme, under the constraints of transmission cost, edge cache size, a quantum particle swarm optimization (QPSO) algorithm is used to solve the data cache placement problem with the greatest content caching gain. A blockchain-based secure decentralized data trading model is proposed to solve the trust problem among the buyers, sellers, and agent nodes and increase incentives for users to trade data. A double auction mechanism is used to maximize social welfare. The experimental results reveal that the proposed data caching and trading scheme can reduce the data transmission cost, improve the cache hit ratio, and maximize social welfare.
Thesis
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This thesis examines the privacy preserving energy management issue, taking into account both energy generation units and responsive demand in the smart grids. Firstly, because of the inherent stochastic behavior of the distributed energy resources, an optimal energy management problem is studied. Distributed energy resources are used in the decentralization of energy systems. Large penetration of distributed energy resources without the precise cybersecurity measures, such as privacy, monitoring and trustworthy communication may jeopardize the energy system and cause outages, and reliability problem for consumers. Therefore, a blockchain based decentralized energy system to accelerate electrification by improving service delivery while minimizing the cost of generation and addressing historical antipathy and cybersecurity risk is proposed. A case study of sub-Sahara Africa is considered. Also, a blockchain based energy trading system is proposed, which includes price negotiation and incentive mechanisms to address the imbalance of order. Besides, the Internet of energy makes it possible to integrate distributed energy resources and consumers. However, as the number of users involved in energy transactions increases, some factors are restricting conventional centralized energy trading. These factors include lack of trust, privacy, fixed energy pricing, and demurrage fees dispute. Therefore, additive homomorphic encryption and consortium blockchain are explored in this thesis to provide privacy and trust. Additionally, a dynamic energy pricing model is formulated based on the load demand response ratio of prosumers to address the fixed energy pricing problem. The proposed dynamic pricing model includes demurrage fees, which is a monetary penalty imposed on a prosumer if it failed to deliver energy within the agreed duration. Also, a new threat model is designed and analyzed. Secondly, mobile prosumers, such as electric vehicles offer a wide range of sophisticated services that contribute to the robustness and energy efficiency of the power grid. As the number of vehicles in the smart grid grows, it potentially exposes vehicle owners to a range of location related privacy threats. For example, when making payments, the location of vehicles is typically revealed during the charging process. Also, fixed pricing policy and lack of trust may restrict energy trading between vehicles and charging stations. Therefore, a private blockchain system is proposed to preserve the privacy of vehicle owners from linking based attack while a public blockchain system is established to enhance energy trading. Various parameters are used to formulate a demand based pricing policy for vehicles, such as time of demand, types of vehicles and locations. Using the demand based pricing policy, an optimal scheduling method is designed to maximize the vehicles both social welfare and utility. An improved consensus energy management algorithm is proposed to protect the privacy of vehicle owners by applying differential privacy. The proposed system is robust against temporal and spatial location based privacy related attacks. Thirdly, blockchain is an evolving decentralized data collection technology, which costeffectively exploits residential homes to collate large amounts of data. The problems of blockchain are the inability to withstand malicious nodes, which provide misleading information that destabilize the entire network, lack of privacy for individual node and shared data inaccuracy. Therefore, a secure system for energy users to share their multi-data using the consortium blockchain is proposed. In this system, a credibility based Byzantine fault tolerance algorithm is employed as the blockchain consensus mechanism to achieve the fault tolerance of the system. Also, a recurrent neural network is used by certain honest users with credibility to forecast the energy usage of other honest users. A recurrent neural network operates on the collated data without revealing the private information about honest users and its gradient parameters. Moreover, additive homomorphic encryption is used in the recurrent neural network to secure the collated data and the gradient parameters of the network. Also, a credibility management system is proposed to prevent malicious users from attacking the system and it consists of two layers: upper and lower. The upper layer manages global credibility that reflects the overall readiness of honest users to engage in multi-data sharing. The lower layer performs local credibility that reflects certain feedback of honest users on the accuracy of the forecast data. Lastly, combining blockchain mining and application intensive tasks increases the computational cost for resource constrained energy users. Besides, the anonymity and privacy problems of the users are not completely addressed in the existing literature. Therefore, this thesis proposes an improved sparse neural network to optimize computation offloading cost for resource constrained energy users. Furthermore, a blockchain system based on garlic routing, known as GarliChain, is proposed to solve the problems of anonymity and privacy for energy users during energy trading in the smart grid. Furthermore, a trust method is proposed to enhance the credibility of nodes in the GarliChain network. Simulations evaluate the theoretical results and prove the effectiveness of the proposed solutions. From the simulation results, the performance of the proposed model and the least-cost option varies with the relative energy generation cost of centralized, decentralized and blockchain based decentralized system infrastructure. Case studies of Burkina Faso, Cote d’Ivoire, Gambia, Liberia, Mali, and Senegal illustrate situations that are more suitable for blockchain based decentralized system. For other sub-Sahara Africa countries, the blockchain based decentralized system can cost-effectively service a large population and regions. Additionally, the proposed blockchain based levelized cost of energy reduces energy costs by approximately 95% for battery and 75% for the solar modules. The future blockchain based levelized cost of energy varies across sub-Sahara Africa on an average of about 0.049 USD/kWh as compared to 0.15 USD/kWh of an existing system in the literature. The proposed model achieves low transaction cost, the minimum execution time for block creation, the transactional data privacy of prosumers and dispute resolution of demurrage fees. Moreover, the proposed system reduces the average system overhead cost up to 66.67% as compared to 33.43% for an existing scheme. Additionally, the proposed blockchain proof of authority consensus average hash power is minimized up to 82.75% as compared to 60.34% for proof of stake and 56.89% for proof of work consensus mechanisms. Simulations are also performed to evaluate the efficacy of the proposed demand based pricing policy for mobile prosumers. From the simulation results, the proposed demand based pricing policy is efficient in terms of both low energy price and average cost, high utility and social welfare maximization as compared to existing schemes in the literature. It means that about 89.23% energy price reduction is achieved for the proposed demand based pricing policy as compared to 83.46% for multi-parameter pricing scheme, 73.86% for fixed pricing scheme and 53.07% for the time of use pricing scheme. The vehicles minimize their operating costs up to 81.46% for the proposed demand based pricing policy as compared to 80.48% for multi-parameter pricing scheme, 69.75% for fixed pricing scheme and 68.29% for the time of use pricing scheme. Also, the proposed system outperforms an existing work, known as blockchain based secure incentive scheme in terms of low energy prices and high utility. Furthermore, the proposed system achieves an average block transaction cost of 1.66 USD. Besides, after applying the differential privacy, the risk of privacy loss is minimum as compared to existing schemes. Furthermore, higher privacy protection of vehicles is attained with a lower information loss against multiple background knowledge of an attacker. To analyze the efficiency of the proposed system regarding multi-data sharing, an experimental assessment reveals that about 85% of honest users share their data with stringent privacy measures. The remaining 15% share their data without stringent privacy measures. Moreover, the proposed system operates at a low operating cost while the credibility management system is used to detect malicious users in the system. Security analysis shows that the proposed system is robust against 51% attack, transaction hacking attack, impersonation attack and the double spending attack. To evaluate the proposed system regarding energy management of resource constrained blockchain energy users, a Jaya optimization algorithm is used to accelerate the error convergence rate while reducing the number of connections between different layers of the neurons for the proposed improved sparse neural network. Furthermore, the security of the users is ensured using blockchain technology while security analysis shows that the system is robust against the Sybil attack. Moreover, the probability of a successful Sybil attack is zero as the number of attackers’ identities and computational capacities increases. Under different sizes of data to be uploaded, the proposed improved sparse neural network scheme has the least average computational cost and data transmission time as compared to deep reinforcement learning combined with genetic algorithm, and sparse evolutionary training and multi-layer perceptron schemes in the literature. Simulation results of the proposed GarliChain system show that the system remains stable as the number of path requests increases. Also, the proposed trust method is 50.56% efficient in detecting dishonest behavior of nodes in the network as compared to 49.20% of an existing fuzzy trust model. Under different sizes of the blocks, the computational cost of the forwarding nodes is minimum. Security analysis shows that the system is robust against both passive and active attacks. Malicious nodes are detected using the path selection model. Moreover, a comparative study of the proposed system with existing systems in the literature is provided.
Thesis
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Instead of planting new electricity generation units, there is a need to design an efficient energy management system to achieve a normalized trend of power consumption. Smart grid has been evolved as a solution, where Demand Response (DR) strategy is used to modify the consumer's nature of demand. In return, utilities pay incentives to the consumer. This concept is equally applicable on residential and commercial areas; however, the increasing load demand and irregular electricity load profile in residential area have encouraged us to propose an efficient home energy management system for optimal scheduling of home appliances. Whereas, electricity consumers have stochastic nature, for which nature-inspired optimization techniques provide optimal solutions. However, these optimization techniques behave stochastically according to the situation. For this reason, we have proposed different optimization techniques for different scenarios. The objectives of this thesis include: reduction in electricity bill and peak to average ratio, minimization of waiting time to start appliances (comfort maximization) and minimization of wastage of surplus energy by exploiting the coordination among appliances and homes. In order to meet the electricity demand of the consumers, the energy consumption patterns of a consumer are maintained through scheduling the appliances in day-ahead and realtime bases. It is applicable by the defined fitness criterion for the proposed hybrid bacterial foraging genetic algorithm and hybrid elephant adaptive cuckoo search optimization techniques, which helps in balancing the load during On-peak and Off-peak hours. Moreover, the concept of coordination and coalition among home appliances is presented for real-time scheduling. The fitness criterion helps the scheduler to optimally decide the ON/OFF status of appliances in order to reduce the waiting time of the appliance. A multi-objective optimization based solution is proposed to resolve the trade-off between conflicting objectives: electricity bill, waiting time of appliances and electricity load shifting according to the defined electricity load pattern. Two optimization techniques: binary multiobjective bird swarm optimization and a hybrid of bird swarm and cuckoo search algorithms are proposed to obtain the Pareto front. The main objective of DR is to encourage the consumer to shift the peak load and gets incentives in terms of cost reduction. However, prices remain the same for all the users even if they shift the peak load or not. In this thesis, Game Theory (GT) based Time of Use pricing model is presented to define the pricing strategy for On-peak and Off-peak hours. The price is defined for each user according to the utilized load using coalitional GT. Further, the proposed pricing model is analyzed for scheduled and unscheduled load. In this regards, Salp swarm and rainfall algorithms are used for scheduling of appliances and an aggregated fitness criterion is defined for load shifting to avoid the peak rebound effect. We also proposed the coordination and coalition based Energy Management System-as-a- Service on Fog (EMSaaS_Fog). With the increase in number of electricity consumers, the computational complexity of energy management system is becoming a threat for efficiency of a system in real-time environment. To deal with this dilemma, the utility shifts computational and storage units on cloud and fog. The proposed EMSaaS_Fog effectively handles the coalition among the apartments within a building to maintain balance between the demand and supply. Moreover, we consider a small community, which consists of multiple smart homes. Microgrid is installed at each residence for electricity generation. It is connected with the fog server to share and store information. Smart energy consumers are able to share detail of excess energy with each other through the fog server.
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Intelligent transportation systems (ITS) can improve the efficiency and safety of transportation. Vehicular Ad Hoc Networks (VANETs) are an important foundation of ITS. However, before being deployed on a large scale, VANETs should resolve the security and privacy issues generated from wireless communication. Digital signature has been used in VANETs to construct anonymous authentication schemes which can realize authentication and privacy preservation. Many previous anonymous authentication schemes have preloaded the master private key into a tamper-proof devices (TPD) which generate the pseudo identity and signature for each vehicle. However, tamper-proof devices cannot defend against side channel attacks. In order to realize better security, this paper takes advantage of lattice-based cryptography to design an anonymous authentication scheme without tamper-proof devices, which achieves security and privacy desired by VANETs. Furthermore, the anonymous authentication scheme lattice based also can defend against quantum computer attack. Finally, the security of this lattice-based anonymous authentication scheme is proven.
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With the exponential growth of technologies such as IoT, edge computing, and 5G, a tremendous amount of structured and unstructured data is being generated from different applications in the smart citiy environment in recent years. Thus, there is a need to develop sophisticated techniques that can efficiently process such huge volumes of data. One of the important components of smart cities, ITS, has led to many applications, including surveillance, infotainment, real-time traffic monitoring, and so on. However, its security, performance, and availability are major concerns facing the research community. The existing solutions, such as cellular networks, RSUs, and mobile cloud computing, are far from perfect because these are highly dependent on centralized architecture and bear the cost of additional infrastructure deployment. Also, the conventional methods of data processing are not capable of handling dynamic and scalable data efficiently. To mitigate these issues, this article proposes an advanced vehicular communication technique where RSUs are proposed to be replaced by edge computing platforms. Then secure V2V and V2E communication is designed using the Quotient filter, a probabilistic data structure. In summary, a smart security framework for VANETs equipped with edge computing nodes and 5G technology has been designed to enhance the capabilities of communication and computation in the modern smart city environment. It has been experimentally demonstrated that use of edge nodes as an intermediate interface between vehicle and cloud reduces access latency and avoids congestion in the backbone network, which allows quick decisions to be made based on the traffic scenario in the geographical location of the vehicles. The proposed scheme outperforms the conventional vehicular models by providing an energy-efficient secure system with minimum delay.
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A vehicular ad-hoc network (VANET) can improve the flow of traffic to facilitate intelligent transportation and to provide convenient information services; where the goal is to provide self-organizing data transmission capabilities for vehicles on the road to enable applications such as assisted vehicle driving and safety warnings. VANETs are affected by issues such as identity validity and message reliability when vehicle nodes share data with other nodes. The method used to allow the vehicle nodes to upload sensor data to a trusted center for storage is susceptible to security risks such as malicious tampering and data leakage. To address these security challenges, we propose a data security sharing and storage system based on the consortium blockchain (DSSCB). This digital signature technique based on the nature of bilinear pairing for elliptic curves is used to ensure the reliability and integrity when transmitting data to a node. The emerging consortium blockchain technology provides a decentralized, secure, and reliable database, which is maintained by the entire network node. In DSSCB, smart contracts are used to limit the triggering conditions for preselected nodes when transmitting and storing data, and for allocating data coins to vehicles that participate in the contribution of data. Security analysis and performance evaluations demonstrated that our DSSCB solution is more secure and reliable in terms of data sharing and storage. Compared with the traditional blockchain system, the time required to confirm the data block was reduced by nearly six times and the transmission efficiency was improved by 83.33%.
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The rapid growth of Internet of Vehicles (IoV) has brought huge challenges for large data storage, intelligent management, and information security for the entire system. The traditional centralized management approach for IoV faces the difficulty in dealing with real time response. The blockchain, as an effective technology for decentralized distributed storage and security management, has already showed great advantages in its application of Bitcoin. In this paper, we investigate how the blockchain technology could be extended to the application of vehicle networking, especially with the consideration of the distributed and secure storage of big data. We define several types of nodes such as vehicle and roadside for vehicle networks and form several sub-blockchain networks. In the paper, we present a model of the outward transmission of vehicle blockchain data, and then give detail theoretical analysis and numerical results. Our study has shown the potential to guide the application of Blockchain for future vehicle networking.
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Carpooling enables passengers to share a vehicle to reduce traveling time, vehicle carbon emissions and traffic congestion. However, the majority of passengers lean to find local drivers, but querying a remote cloud server leads to an unnecessary communication overhead and an increased response delay. Recently, fog computing is introduced to provide local data processing with low latency, but it also raises new security and privacy concerns because users’ private information (e.g., identity, location) could be disclosed when theses information are shared during carpooling. While they can be encrypted before transmission, it makes user matching a challenging task and malicious users can upload false locations. Moreover, carpooling records should be kept in a distributed manner to guarantee reliable data auditability. To address these problems, we propose an efficient and privacy-preserving carpooling scheme using blockchain-assisted vehicular fog computing to support conditional privacy, one-to-many matching, destination matching and data auditability. Specifically, we authenticate users in a conditionally anonymous way. Also, we adopt private proximity test to achieve one-to-many proximity matching and extend it to efficiently establish a secret communication key between a passenger and a driver. We store all location grids into a tree and achieve get-off location matching using a range query technique. A private blockchain is built to store carpooling records. Finally, we analyze the security and privacy properties of the proposed scheme, and evaluate its performance in terms of computational costs and communication overhead. IEEE
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With the dramatically increasing deployment of IoT devices, storing and protecting the large volume of IoT data has become a significant issue. Traditional cloud-based IoT structures impose extremely high computation and storage demands on the cloud servers. Meanwhile, the strong dependencies on the centralized servers bring significant trust issues. To mitigate these problems, we propose a distributed data storage scheme employing blockchain and cetrificateless cryptography. Our scheme eliminates the traditional centralized servers by leveraging the blockchain miners who perform "transaction" verifications and records audit with the help of certificateless cryptography. We present a clear definition of the transactions in a non-cryptocurrency system and illustrate how the transactions are processed. To the best of our knowledge, this is the first work designing a secure and accountable IoT storage system using blockchain. Additionally, we extend our scheme to enable data trading and elaborate how data trading can be efficiently and effectively achieved.
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With the development of network technology and cloud computing, data sharing is becoming increasingly popular, and many scholars have conducted in-depth research to promote its flourish. As the scale of data sharing expands, its privacy protection has become a hot issue in research. Moreover, in data sharing, the data is usually maintained in multiple parties, which brings new challenges to protect the privacy of these multi-party data. In this paper, we propose a trusted data sharing scheme using blockchain. We use blockchain to prevent the shared data from being tampered, and use the Paillier cryptosystem to realize the confidentiality of the shared data. In the proposed scheme, the shared data can be traded, and the transaction information is protected by using the (p, t)-threshold Paillier cryptosystem. We conduct experiments in cloud storage scenarios and the experimental results demonstrate the efficiency and effectiveness of the proposed scheme.
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Blockchain technology has the potential to transform healthcare delivery by facilitating data sharing between providers and electronic health record (EHR) systems. However, significant roadblocks stand in the way of widespread implementation of this technology across the healthcare industry. Our blockchainbased data-sharing solution addresses two of the most critical challenges associated with using blockchain for health data sharing: protecting sensitive health information and deploying and installing blockchain software across diverse hospital environments. Since transparency is a fundamental feature of blockchain, we enabled user- and group-based secret sharing by adding purpose-built software that leverages a collection of well-established cryptographic algorithms. To streamline deployment, we built a containerized solution that guarantees portability, simplifies installation, and reduces overhead maintenance costs associated with administration. To ensure ease of implementation in a hospital system, we designed our blockchain solution using a distributed microservices architecture that allows us to encapsulate core functions of our system into isolated services that can be scaled independently based on the requirements of a particular hospital system deployment. As part of this architecture, we built core components for securely handling cryptographic secrets, interacting with blockchain nodes, facilitating large file sharing, enabling secondary-index based lookups, and integrating external business logic that governs how users interact with Smart Contracts. The innovative design of our blockchain solution, which addresses critical data security, deployment, and installation challenges, provides the healthcare community with a unique approach that has the power to connect providers while protecting sensitive data. Keywords: Blockchain, Data Sharing, Data Exchange, EHR,electronic health record, Ethereum, interplanetary file system, IPFS
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Existing secure and privacy-preserving vehicular communication protocols in vehicular ad hoc networks face the challenges of being fast and not depending on ideal tamper-proof devices (TPDs) embedded in vehicles. To address these challenges, we propose a vehicular authentication protocol referred to as distributedaggregate privacy-preserving authentication. The proposed protocol is based on our new multiple trusted authority one-time identity-based aggregate signature technique. With this technique a vehicle can verify many messages simultaneously and their signatures can be compressed into a single one that greatly reduces the storage space needed by a vehicle or a data collector (e.g., the traffic management authority). Instead of ideal TPDs, our protocol only requires realistic TPDs and hence is more practical.
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A purely peer-to-peer version of electronic cash would allow online payments to be sent directly from one party to another without going through a financial institution. Digital signatures provide part of the solution, but the main benefits are lost if a trusted third party is still required to prevent double-spending. We propose a solution to the double-spending problem using a peer-to-peer network. The network timestamps transactions by hashing them into an ongoing chain of hash-based proof-of-work, forming a record that cannot be changed without redoing the proof-of-work. The longest chain not only serves as proof of the sequence of events witnessed, but proof that it came from the largest pool of CPU power. As long as a majority of CPU power is controlled by nodes that are not cooperating to attack the network, they'll generate the longest chain and outpace attackers. The network itself requires minimal structure. Messages are broadcast on a best effort basis, and nodes can leave and rejoin the network at will, accepting the longest proof-of-work chain as proof of what happened while they were gone.
Conference Paper
We propose a fully functional identity-based encryption scheme (IBE). The scheme has chosen ciphertext security in the random oracle model assuming an elliptic curve variant of the computational Diffie-Hellman problem. Our system is based on the Weil pairing. We give precise definitions for secure identity based encryption schemes and give several applications for such systems.